We develop a new completely affine model of the term structure of interest rates, in which the statevariables evolve as a matrix-valued process of stochastically correlated factors. This setting grants a newelement of flexibility in the simultaneous modeling of stochastic volatilities and...

We develop infinitesimally robust statistical procedures for general diffusion pro-cesses. We first prove existence and uniqueness of the times series influence functionof conditionally unbiased M{estimators for ergodic and stationary diffusions, underweak conditions on the (martingale)...

We study how the interaction of agents with different beliefs about a firm’s future cash flows determines the jointbehavior of credit spreads, option implied volatilities, and stock returns. Beliefs heterogeneity influences the pricing kernelin a way that supports more realistic credit spreads...

This paper suggests that changing risk conveys information useful to improve performance.

Control problems with Recursive Multiple-Priors Utility (RMPU) are highly non-linear so that RMPU asset prices have been studied in very simple exchange economies only. We identify a continuous-time exchange equilibrium with Locally-Constrained-Entropy RMPU (LCE-RMPU) that is tractable even in...

We propose a new multivariate GARCH model with Dynamic Conditional Correlations that extends previous models by admitting multivariate thresholds in conditional volatilitiesand correlations. The model estimation is feasible in large dimensions and the positive definiteness of the conditional...

We propose a multivariate nonparametric technique for generating reliable short-term historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest...

We apply perturbation theory to solve the optimal control problem of an investor with time-additive power utility over intermediate consumption and final wealth. Under general conditions we show existence of a power series representation for the prevailing optimal consumption and investment...

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

We study the problem of learning the probability distribution of a multinomial variable from an observed sequence of signals, starting in a condition of ignorance about this distribution. We show that not all signals are suited for producing non-vacuous inferences under prior ignorance. To...